Triple
T17709869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sviatoshynsko–Brovarska line |
E441533
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object |
Darnytsia depot
Darnytsia depot is a maintenance and storage facility serving trains on the Kyiv Metro’s Sviatoshynsko–Brovarska line.
|
E1285381
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Darnytsia depot | Statement: [Sviatoshynsko–Brovarska line, hasDepot, Darnytsia depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darnytsia depot Context triple: [Sviatoshynsko–Brovarska line, hasDepot, Darnytsia depot]
-
A.
Kholodna Hora depot
Kholodna Hora depot is a maintenance and storage facility serving the Kharkiv Metro system in Kharkiv, Ukraine.
-
B.
Mogilevskoe depot
Mogilevskoe depot is a maintenance and storage facility serving the rolling stock of the Minsk Metro system in Belarus.
-
C.
Moskovskoe depot
Moskovskoe depot is a maintenance and storage facility serving the Minsk Metro system in Minsk, Belarus.
-
D.
Zelenoluzhskoe depot
Zelenoluzhskoe depot is a maintenance and storage facility serving trains of the Minsk Metro system in Minsk, Belarus.
-
E.
Kharkiv railway junction
Kharkiv railway junction is a major rail transport node in eastern Ukraine that connects key national and international railway routes through the city of Kharkiv.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Darnytsia depot Triple: [Sviatoshynsko–Brovarska line, hasDepot, Darnytsia depot]
Generated description
Darnytsia depot is a maintenance and storage facility serving trains on the Kyiv Metro’s Sviatoshynsko–Brovarska line.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Darnytsia depot Target entity description: Darnytsia depot is a maintenance and storage facility serving trains on the Kyiv Metro’s Sviatoshynsko–Brovarska line.
-
A.
Kholodna Hora depot
Kholodna Hora depot is a maintenance and storage facility serving the Kharkiv Metro system in Kharkiv, Ukraine.
-
B.
Mogilevskoe depot
Mogilevskoe depot is a maintenance and storage facility serving the rolling stock of the Minsk Metro system in Belarus.
-
C.
Moskovskoe depot
Moskovskoe depot is a maintenance and storage facility serving the Minsk Metro system in Minsk, Belarus.
-
D.
Zelenoluzhskoe depot
Zelenoluzhskoe depot is a maintenance and storage facility serving trains of the Minsk Metro system in Minsk, Belarus.
-
E.
Kharkiv railway junction
Kharkiv railway junction is a major rail transport node in eastern Ukraine that connects key national and international railway routes through the city of Kharkiv.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8b9ea20b48190ace88bb46b01e6a9 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4729a9a9c81908d65ff0bda12c961 |
completed | April 19, 2026, 6:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0242edd438819089b8c23ff79c822e |
completed | May 11, 2026, 8:58 p.m. |
| NEDg | Description generation | batch_6a02455730948190b1151d24f260d768 |
completed | May 11, 2026, 9:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0245c34d008190ae029000dc8e9cbc |
completed | May 11, 2026, 9:10 p.m. |
Created at: April 10, 2026, 10:05 a.m.